Long memory and nonlinearities in realized volatility: a Markov switching approach
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Publication:1927150
DOI10.1016/j.csda.2010.12.008zbMath1255.62321OpenAlexW2033780024MaRDI QIDQ1927150
Davide Raggi, Silvano Bordignon
Publication date: 30 December 2012
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: http://amsacta.unibo.it/4547/1/694.pdf
Applications of statistics to actuarial sciences and financial mathematics (62P05) Numerical analysis or methods applied to Markov chains (65C40)
Related Items (4)
When long memory meets the Kalman filter: a comparative study ⋮ Infinite-order, long-memory heterogeneous autoregressive models ⋮ Realized stochastic volatility with leverage and long memory ⋮ Particle Gibbs with ancestor sampling for stochastic volatility models with: heavy tails, in mean effects, leverage, serial dependence and structural breaks
Uses Software
Cites Work
- Unnamed Item
- Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
- A multiple regime smooth transition heterogeneous autoregressive model for long memory and asymmetries
- Simulation-based sequential analysis of Markov switching stochastic volatility models
- Volatility forecasting using threshold heteroskedastic models of the intra-day range
- Calculating posterior distributions and modal estimates in Markov mixture models
- Autoregressive conditional heteroskedasticity and changes in regime
- Bayesian analysis of long memory and persistence using ARFIMA models
- State space modeling of long-memory processes
- Bayesian estimation of switching ARMA models
- Varieties of long memory models
- Real time detection of structural breaks in GARCH models
- Forecasting volatility under fractality, regime-switching, long memory and Student-\(t\) innovations
- Bayesian wavelet analysis of autoregressive fractionally integrated moving-average processes
- Finite mixture and Markov switching models.
- Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices
- Forecasting Stock Market Volatility with Regime-Switching GARCH Models
- Bayesian methods for change-point detection in long-range dependent processes
- Long‐Memory Time Series
- Microstructure Noise, Realized Variance, and Optimal Sampling
- Realized Volatility: A Review
- Bayesian estimation of a Markov-switching threshold asymmetric GARCH model with Student-t innovations
- A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
- Bayesian analysis of autoregressive fractionally integrated moving-average processes
- A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle
- Partial non-Gaussian state space
- STATISTICAL ANALYSIS OF ECONOMIC TIME SERIES VIA MARKOV SWITCHING MODELS
- On Gibbs sampling for state space models
- Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
- Bayesian Measures of Model Complexity and Fit
- Reversible Jump Markov Chain Monte Carlo Strategies for Bayesian Model Selection in Autoregressive Processes
- The Distribution of Realized Exchange Rate Volatility
- Markov chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models
- Likelihood‐based Analysis of a Class of Generalized Long‐Memory Time Series Models
- Bayesian analysis of switching ARCH models
- Modeling and Forecasting Realized Volatility
- Long memory and regime switching
- Deviance information criteria for missing data models
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